Multiple ecossystem services and socio-economic data about Matopiba municipalities - Brazil
Description
This database contains values for raw and normalized ES proxies, alongside socio-economic and deforestation indicators and statistical analysis results. The study area covered the 337 municipalities of the MATOPIBA region in Brazil.
Files
Steps to reproduce
The methodology comprised three major steps: 1) ES classification and proxies selection; 2) Data processing and mapping of ES proxies; 3) Integration analysis of ES proxies and other indicators - i) Current ES supply analysis and correlation by category and total by municipality, ii) Synergies and trade-offs analysis, iii) ES bundles analysis, and iv) Building Rural Sustainability Map for MATOPIBA municipalities. Data related to the ES proxies of the ES selected and classified were pre-processed an Excel spreadsheet and were later imported in shapefile or matrix format and processed in the geographic information system software ArcGIS 10.8.2 and QGIS 3.34.4, standardising the cartographic projection to the geographic coordinate system, SIRGAS2000 and generating a thematic map for each indicator. The shapefiles and matrix data were initially cropped and adjusted to the limits of the study area. The mapping for the selected ES was carried out for the 337 MATOPIBA municipalities. To integrate ES proxies maps into GIS and analyse ES supply, correlation, synergies, trade-offs, bundles, and to build Rural Sustainability Map, the first step was to normalise the ranges of all ES proxies. For all ES maps generated, the data (between the lowest and highest values presented for the study area) were grouped into five classes (using the ArcGIS Natural Breaks classification - Jenks, 1967). This method seeks to reduce the variance within classes and maximize the variance between classes. Next, the classes were reclassified from 1 to 5, considering that 1 has the lowest contribution and 5 the highest contribution to ES supply. The exceptions are the proxies for erodibility and distance from forest fragments—where higher values indicate a poorer contribution to the provision ES —a fact taken into account during the spatialization of the data. It was decided to separate the food provision into two categories (food for local supply and for export), understanding that these represent products that need to be differentiated, especially when taking into account the regional food supply. For raster data (water balance and soil erodibility) it was necessary to use zonal statistics to generate only one value for each municipality, using the QGIS zonal statistics tool. The first integration was performed among the ES proxies to generate the ES supply maps by category (provision, regulation and biodiversity maintenance and cultural), using the shapefile of municipalities and related to it the attribute/indicator table with their reclassified values (1 to 5). A weight of 1 was maintained for all proxies (attributes in the table), with the exception of the % CU indicator, which received a weight of 2, because it is very important for both regulation and biodiversity maintenance, as well for cultural ES. A Field Calculator was used in ArcGIS 10.8.2, summing proxy values (1 to 5) and after spatialising the results into five classes based on Natural Breaks method.
Institutions
- Brazilian Agricultural Research CorporationFederal District, Brasília
Categories
Funders
- Brazilian Agricultural Research CorporationFederal District, Brasília